Course Details

  • Date: February 9th, 2016 - February 9th, 2016
  • Time: 9:30 am - 4:30 pm
  • Location:
  • Presenter(s): Matthew Wampole (Clarivate Analytics)

BTEP Workshop on Pathway Analysis with MetaCore

NOTE:This is a Bring Your Own Computer (BYOC) class, and will be simultaneously shared via GoToMeeting with attendees at the Advanced Technology Research Facility (ATRF) in Frederick, MD. Kindly select the location you plan to attend at the top of the registration page.

Date: February 9, 2016 (Tuesday)
Time: 9:30 am – 12:30 pm and 1:30 – 4:30 pm

Two Venues:

Live Workshop – NIH Bethesda – Bldg 10, FAES Room 7 (B1C206)
Remote Simulcast – ATRF, Room E1106 – 8560 Progress Dr, Frederick, MD

For more information on the Frederick simulcast, please contact:
Tracie Frederick, Technology Informationist, Scientific Library
Phone: 301-846-1094
Email: frederickt@mail.nih.gov


AGENDA

Tuesday, February 9, 2016 – Pathway Analysis with MetaCore

MetaCore is an integrated curated knowledge database and software suite for pathway analysis of experimental data and gene lists. The scope of data types includes microarray and sequence-based gene expression, SNPs and CGH arrays, RNAi screens, gene variants, proteomics, metabolomics, Co-IP pull-out and other custom interactions which can all by analyzed in tandem. MetaCore is based on a proprietary manually curated database of human protein-protein, protein-DNA and protein-compound interactions, metabolic and signaling pathways for human, mouse and rat, supported by proprietary ontologies and controlled vocabulary. The analytical package includes easy-to-use, intuitive tools for searching and data visualization, enabling the identification of the most relevant biological pathways, networks, and processes in our “virtual lab.”

The core functionalities in MetaCore that will be covered include:

  • Key Pathway Advisor to find drivers of expression change from transcriptomic data
  • Expression data upload, filtering, and setting experimental backgrounds
  • Knowledge mining for information about a gene or disease
  • Basic enrichment and Comparison analysis